1. Field of the Invention
Embodiments of the present invention generally relate to analysis of Computed Tomography (“CT”) images, and particularly to CT systems used for detection of explosives.
2. Description of the Related Art
Some baggage inspection systems utilize transmission x-ray images at one or more angles. In some known computed tomography (“CT”) imaging system configurations, an X-ray source projects a fan-shaped or a cone-shaped beam, which is collimated to hit a linear or two-dimensional array of detectors. The X-ray beam passes through an object being imaged. The beam, after being attenuated by the object, impinges upon an array of radiation detectors. Each detector element of the array produces a separate electrical signal that is a measurement of the beam intensity at the detector location. During data acquisition, a gantry rotates around a tunnel with an X-ray emitter.
Some explosive detection systems utilize CT technology to produce CT images that represent a cross section, or slice, through the object. A CT image consists of an array of pixels. Each pixel has a value representing the x-ray attenuation of the image object at that point in the image. X-ray attenuation can be used as an approximation of density. Pixel values in a CT image are referred to as “CT Numbers” and are often in Hounsfield units.
Some CT based systems use a transmission image plus a limited number of CT slices to determine the density and volume of objects. These systems are referred to as “sparse slicing systems”. In some cases, the transmission image is acquired using a tube and detector assembly mounted on a rotating gantry. The gantry rotates around the object while the object passes through the gantry, producing a twisted transmission image.
In other CT based systems, CT slices are produced at regular, closely spaced intervals so that the entire volume of an object is imaged. These scanners are referred to as volume scanners. Each pixel in each CT slice therefore represents a volume, and is often called a voxel. The value of each voxel represents an approximation of the density of the object within the voxel. Each voxel represents X-ray attenuation and is related to object density and effective atomic number. Many volume scanners employ multiple rows of detectors arranged in an array, and an object is moved continuously through the gantry while the gantry rotates. These scanners are called spiral or helical scanners.
CT scanners can accurately produce CT numbers for large objects. However, as objects become smaller or thinner, the accuracy of the CT number decreases. The accuracy of the CT number is limited by the spatial resolution of the scanner. The spatial resolution of the scanner is determined by the size of the x-ray source, the size of the detectors, the number of views acquired, and convolution filters used in CT image reconstruction. For helical scanners, the pitch of the scanner also influences the resolution. Pitch is the speed that the object moves through the scanner in relation to the rotational speed of the gantry and the width of the detector array.
CT number accuracy is further limited by the size of the pixel or voxel. If the pixel is large compared to the object being imaged and the object covers only half the area of the pixel, the CT number will represent the average linear attenuation of the object and the surrounding material. Furthermore, because of the nonlinear nature of CT transmission (as opposed to, e.g., emission tomography), the CT number for voxels that contain mixtures of materials is a nonlinear function of the total attenuation, a phenomenon known as Nonlinear Partial Volume.
Some approaches in the prior art (e.g., U.S. Pat. No. 6,026,143 issued Feb. 15, 2000) utilize erosion of the exterior surface of an object as a way of discovering the true CT number of the object. If the object is surrounded by low density material, such as air, the voxels on the exterior surface will be lower than the interior voxels. Erosion is an image processing technique for removing the exterior voxels from an object. Once the surface is eroded, the remaining voxels have a CT number that is closer to the true CT number of the object. After the interior CT number is known, the object is dilated, or the eroded pixels are added back into the object, but the CT number of the previously eroded pixels is changed to be equal to the interior CT number. The problem with this approach is that as the thickness of an object approaches the spatial resolution of the CT system, the interior pixels no longer reflect the true CT number of the object. In the prior art, voxels are identified as belonging to sheet objects, bulk objects, or background. Then objects are built from connected voxels of the same type to form sheet or bulk objects. Thereafter, sheet objects and bulk objects are treated differently, including using different density and mass thresholds to determine whether an object is benign or is a threat. The problem with this approach is that both bulk and sheet explosives can be made of the same material, and it is easily possible to form a single object from plastic explosives that is thin in parts and thick in other parts, and thereby appearing to be part sheet and part bulk. This could cause misclassification of the object and also could cause a single object to be segmented into separate pieces, each of which is too small to cause an alarm.
Therefore, there is a need in the art for improved detection and analysis of thin objects in CT systems.